This tutorial implements computer models of the Radio-ML ConvNet in Python using Jupyter Notebooks. This is best managed using a Python virtual environment.
The first step of this tutorial involves setting up such a virtual environment with the required versions of all the associated open source Python packages.
The top level Makefile of this tutorial builds the Python virtual environment based on a script create_venv.sh. It creates the environment and then loads a set of specific versions of all required Python packages.
To create this Python virtual environment, run the following code:
% make venv
% source my-venv/bin/activate
% python --version
This creates a folder my-venv in the top-level folder. This folder contains all the required packages for Jupyter Notebooks, TensorFlow, matplotlib, pydot, and bfloat16 (including all dependencies) required by the tutorial.
The second command activates the Python environment. The third command displays the version of Python used to create the virtual environment. This tutorial is and tested using Python 3.12.6.